HVE Core is a collection of agents, prompts, coding instructions, and skills for building repeatable software-development workflows with GitHub Copilot. It is intended for individuals and teams that want structured AI-assisted research, planning, implementation, and review, while the catalogue entries provide many of its reusable workflow components.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add microsoft/hve-core --skill rpi-plan-critiquegit clone --depth 1 https://github.com/microsoft/hve-coreWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/microsoft/hve-core/rpi-plan-critique)<a href="https://agentmods.dev/skills/microsoft/hve-core/rpi-plan-critique"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/rpi-plan-critique/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/microsoft/hve-core/rpi-plan-critique"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/rpi-plan-critique.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 62 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 66 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.02224 |
| Opus 5.5 | $0.00016 | $0.00890 |
| Sonnet 5.5 | $0.00008 | $0.00445 |
| Haiku 4.5 | $0.00004 | $0.00222 |
Grade A, and why
rpi-plan-critique scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RPI Plan Critique
Goal
Return one substantive, evidence-grounded credibility assessment of an RPI implementation plan. Assess the plan against the supplied evidence with fresh eyes rather than the drafting reasoning, through lens assessments merged into one finding set, as quickly as the supplied evidence permits. The critique is read-only with respect to the plan and writes only the caller-specified critique artifact.
Flow
- Confirm the task identity, plan, evidence, requirements, decisions, dependencies, task Requirements, critique output path, critique depth, and any lens reasoning effort supplied by the caller. Use
standardwhen depth is omitted. Usedeeponly when the caller records explicit user direction; otherwise downgrade an unsupported deep request to standard and record the limitation. Standalone use needs only these inputs; no planning parent is required. - Read the plan's headings and its phase, task, and requirement IDs, plus the earlier critique when one is supplied. Do not read unsupplied artifacts, perform open-ended research, browse for additional concerns, or infer missing evidence as fact.
- Before any lens runs, write the critique record at the output path from templates/plan-critique.md with
Critique execution: started, the inputs and boundary, and one Lens Assessments row per lens with statusqueued. The record grows as the critique runs, so a reader can follow it while it runs. - Decide who assesses the lenses, following references/lens-assessment.md.
- When the plan has more than one phase, a dispatch tool is available, and the user's subagent direction allows lens subagents, dispatch the lenses to
RPI Plan Critic. Without assessing the plan yourself, choose the lenses and their scope from those IDs, select each lens's reasoning effort, using the user's or caller's level when one is set and otherwise the level the lens's work needs, and send every lens in one parallel batch. The reference covers the fallback whenRPI Plan Criticis unavailable. - Otherwise, assess each lens yourself, one at a time, with the same lens questions. Set a lens's row to
in progresswhen you start it.
- When the plan has more than one phase, a dispatch tool is available, and the user's subagent direction allows lens subagents, dispatch the lenses to
- Merge each lens's result as it finishes, as Merge the returns describes: set its row's status, add its verified findings under Findings, merge a duplicate into the finding already recorded, and save the record before the next lens or return. The merged set covers the full boundary across requirements, research, phase and task Goals, task Requirements, Details, References, dependencies, decisions, risks, and missed concerns. For a follow-up critique, mark each earlier finding resolved, still open, or superseded against the current plan rather than repeating it, and add new findings for gaps the revision introduced.
- Assess coverage across the supplied plan and evidence as a whole. Do not require a task to repeat requirements already established elsewhere solely for restatement. A stated requirement alone does not prove implementation coverage; ground required changes in demonstrated omissions, contradictions, or material evidence gaps.
- Treat missing detail in an abbreviated task or excerpt as a limitation of the supplied evidence, not proof that the full plan omits it. Identify the evidence needed to resolve a decision-critical uncertainty; do not turn the same uncertainty into a separate requirement-restatement finding.
- In
standard, assess the complete supplied boundary while prioritizing implementation blockers, contradictions, missing dependencies or acceptance coverage, unsupported scope or architecture, and material risks. Follow direct evidence and omit plan restatement, exhaustive strengths, and low-impact suggestions so the complete evidence-supported actionable set is recorded with minimal elapsed work. - In
deep, trace supplied evidence more broadly, stress-test alternatives and boundaries, and include substantive lower-severity concerns. Deep remains one assessment and does not widen research authority. - In either depth, return one complete finding set rather than serializing findings across critique passes. Findings land one lens at a time, but the critique is still one assessment with one verdict.
- Complete the record using templates/plan-critique.md, including each lens's scope, reasoning effort and its source, status, and adopted and rejected candidates under Lens Assessments, then the coverage assessment, verdict, strengths, questions, limitations, and next action. Use
PC-xxxfindings keyed to relevant requirement, research, phase, or task IDs, graded on the severity scale in references/lens-assessment.md, and fill every field the template gives an actionable finding. A follow-up critique continues the earlierPC-xxxnumbering. - Record critique execution as Complete, Partial, Blocked, or Not produced, separately from its Pass, Revise, or Blocked verdict; execution leaves
startedonly when the record is complete. When no assessment was produced, record execution Not produced and verdict unavailable, preserve any fragments, and return the limitation; never manufacture a verdict. A passing critique may identify residual risks the parent explicitly accepted.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago Changed · +1 lines 59720bafd9bd
- 19d ago Changed · +2 lines f318958497e4
- 1mo ago Changed · -9 lines · +2 tokens per session 670053724a7a
- 1mo ago Changed · +1 lines · +3 tokens per session cc0c55bce6ed
- 1mo ago Changed 439d2d57c56d
- 1mo ago Changed · +10 lines 034c397bf88e
- 2mo ago Changed · +10 lines · -1 tokens per session b47413c667ba
- 2mo ago First seen · 73 lines · 36 tokens per session scan A c943c68cd045
rpi-plan-critique is a skill published in the GitHub repository microsoft/hve-core (1,606 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 2,224 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
rpi-plan-critique compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| rpi-plan-critiquemicrosoft/hve-core | Skill | 1.6k | today | MIT | A | 40 | Claude Code |
| autoreviewopenclaw/clawhub | Skill | 9.6k | today | MIT | A | 17 | Claude Code, Codex |
| agent-teams-simplify-and-hardenLeoYeAI/openclaw-master-skills | Skill | 2.2k | 2d ago | MIT | A | 115 | Claude Code, Codex |
| omh-code-reviewrlaope/oh-my-hermes | Skill | 5.2k | today | MIT | A | 49 | Claude Code, Codex |
| revdiff-planumputun/revdiff | Skill | 947 | 3d ago | MIT | A | 84 | Claude Code |
| explore-unknownsdzhng/skills | Skill | 1.5k | today | MIT | A | 162 | Claude Code, Codex |
| re0-mergeLilMGenius/paperthin | Skill | 1.4k | today | MIT | A | 70 | Claude Code |